Adaptive Fuzzy Output Feedback Control based on Observer for Nonlinear Heating, Ventilating and Air Conditioning System

Baek, Jaeho; Hwang, Eun Ju; Kim, Euntai; Park, Mignon

doi:10.5391/ijfis.2009.9.2.076

Cited by 4 publications

(5 citation statements)

References 13 publications

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“…Fuzzy logic controllers also offer a potential solution, coupling and integrating the management of all the different criteria and components of an HVAC system. Authors in [9], proposed an adaptive fuzzy output feedback controller, based on an observer for the HVAC system. A fuzzy controller for HVAC system of an automobile cabin is developed in [10].…”

Section: A Control Approachesmentioning

confidence: 99%

A Dynamic Programming Approach for Thermal Comfort Control in Electric Vehicles

Lahlou¹,

Ossart

Boudard³

et al. 2018

2018 IEEE Vehicle Power and Propulsion Conference (VPPC)

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The HVAC system represents the main auxiliary load in electric vehicles (EVs) and requires efficient control approaches that balance energy saving and thermal comfort. In fact, passengers always demand more comfort, but on the other hand the HVAC system consumption strongly impacts the vehicle driving range, which constitutes the major concern in EVs. In this paper, dynamic programing is applied to develop an HVAC system supervisor that optimizes the thermal comfort on a given journey, for given climatic conditions and energy available. The electric vehicle model and the optimization approach are presented. Two test-cases, corresponding to hot climate, are simulated. In the first one, the energetic cost of improved comfort is quantified, while in the second one the trade-off between driving speed and thermal comfort is analyzed.

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Section: A Control Approachesmentioning

confidence: 99%

A Dynamic Programming Approach for Thermal Comfort Control in Electric Vehicles

Lahlou¹,

Ossart

Boudard³

et al. 2018

2018 IEEE Vehicle Power and Propulsion Conference (VPPC)

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“…System identification and state space model for one AHU of the S. J. Carew Building was presented without control [17]. In earlier studies, researchers investigated mainly humidity and temperature levels in modeling HVAC systems [18][19][20][21][22]. A nonlinear HVAC model was introduced [18,19] that involves a temperature/humidity ratio and an observer for determining approximate moisture and thermal loads.…”

Section: Control Strategiesmentioning

confidence: 99%

“…A nonlinear HVAC model was introduced [18,19] that involves a temperature/humidity ratio and an observer for determining approximate moisture and thermal loads. An adaptive fuzzy output feedback controller was developed [20] that can be premised on an HVAC system observer. Researchers proposed applying both a decentralized nonlinear adaptive controller [21].…”

Section: Control Strategiesmentioning

confidence: 99%

Modeling, Analysis, and State Feedback Control Design of a Multizone HVAC System

2018

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A HVAC system is modeled by applying a state space MIMO (multi-input/multioutput) system method for control system design and analysis. Thermal models are developed using the simulation program IDA Indoor Climate and Energy. The building has four floors in total, with separate air-handling units (AHUs) on each floor. The system’s eight main input data are hot water and the energy usage for each AHU, while the eight main outputs are return airflow temperature and CO2 levels for AHUs. The factors of wind direction and velocity are also applied as disturbances. By comparing usage data on simulated power consumption versus measured data for the three months of October, November, and December 2016, good agreement was achieved with simulated data. The main aim is to develop a state feedback controller and then apply it toward optimal functionality of a control system. After utilizing the MATLAB identification toolbox, a MIMO system-based state space model is developed.

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“…In most previous studies, HVAC systems have been modeled considering only the temperature and the humidity ratio [5][6][7][8]. A nonlinear HVAC model that includes dynamics of temperature and humidity ratio is proposed in [5], which includes the design of an observer to estimate the thermal and moisture loads.…”

Section: Introductionmentioning

confidence: 99%

“…A nonlinear HVAC model that includes dynamics of temperature and humidity ratio is proposed in [5], which includes the design of an observer to estimate the thermal and moisture loads. In [6], an adaptive fuzzy output feedback controller is proposed, based on an observer for the HVAC system. In [7,8], a back-stepping controller and a decentralized nonlinear adaptive controller are respectively applied to the same model.…”

Section: Introductionmentioning

confidence: 99%

Novel Modeling and Control Strategies for a HVAC System Including Carbon Dioxide Control

Kang

Park

et al. 2014

Energies

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Conventional heating, ventilating, and air conditioning (HVAC) systems have traditionally used the temperature and the humidity ratio as the quantitative indices of comfort in a room. Recently, the carbon dioxide (CO 2 ) concentration has also been recognized as having an important contribution to room comfort. This paper presents the modeling of an augmented HVAC system including CO 2 concentration, and its control strategies. Because the proposed augmented HVAC system is multi-input multi-output (MIMO) and has no relative degree problem, the dynamic extension algorithm can be employed; then, a feedback linearization technique is applied. A linear-quadratic regulator (LQR) is designed to optimize control performance and to stabilize the proposed HVAC system. Simulation results are provided to validate the proposed system model, as well as its linearized control system.

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Adaptive Fuzzy Output Feedback Control based on Observer for Nonlinear Heating, Ventilating and Air Conditioning System

Cited by 4 publications

References 13 publications

A Dynamic Programming Approach for Thermal Comfort Control in Electric Vehicles

A Dynamic Programming Approach for Thermal Comfort Control in Electric Vehicles

Modeling, Analysis, and State Feedback Control Design of a Multizone HVAC System

Novel Modeling and Control Strategies for a HVAC System Including Carbon Dioxide Control

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